Abstract
Aims
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Expression defects and turnover of basement membrane (BM) proteins are key pathogenic factors in cancer. It is still uncertain how the expression of BM-related genes (BMGs) in HCC relates to prognosis.
Methods
All of the HCC cohort's RNA-seq and clinical information came from TCGA datasets. The least absolute shrinkage and selection operator (LASSO) regression algorithm was utilized to filter down the candidate genes and construct the prognostic model. Univariate and multivariate Cox analyses were run to examine if the risk score may serve as a standalone prognostic indicator. The single-sample gene set enrichment analysis (ssGSEA) was utilized to analyze examine immune cell infiltration and pathway activity.
Results
Five genes and their risk coefficients were eventually identified and patients with HCC were classified as either high or low risk based on the median of risk scores. Multivariate Cox regression analysis found a significant correlation between risk score and OS (p < 0.001). Subgroup analysis showed that BMGs signature had good prediction ability for HCC patients in age, gender, T stage, and AJCC stage (all p < 0.05). According to the ssGSEA, the high-risk subgroup showed higher levels of immune cell infiltration and immune-related pathways were more engaged in the high-risk group.
Conclusions
Our research systematically built a prognostic model using risk score based on BMGs signature in HCC patients. The immune feature analysis of the BMGs signature indicated a potential regulation between tumor immunity and BM in HCC.
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Data availability
Our data are from the analysis of articles and can be provided when necessary.
Abbreviations
- HCC:
-
Hepatocellular carcinoma
- BM:
-
Basement membrane
- BMGs:
-
BM-related genes
- LASSO:
-
Least absolute shrinkage and selection operator
- ssGSEA:
-
Single-sample gene set enrichment analysis
- TKIs:
-
Tyrosine kinase inhibitors
- ICIs:
-
Immune checkpoint inhibitors
- ECM:
-
Extracellular matrix
- TME:
-
Tumor microenvironment
- PPI:
-
Protein–protein interaction
- GO:
-
Gene Ontology
- KEGG:
-
Kyoto Encyclopedia of Genes and Genomes
- DEGs:
-
Differentially expressed genes
- CTSA:
-
Cathepsin A
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Acknowledgements
This work was supported by the "Natural Science Foundation of Fujian Province, China" (No. 2020J011264), which provided funds for research to Hongbin Chen. The authors thank Dr. Yingming Sun for providing technical guidance.
Funding
This work was supported by the "Natural Science Foundation of Fujian Province, China" (No. 2020J011264), which provided funds for research to Hongbin Chen.
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HC and YZ in designed the study. YZ and ZY conducted the bioinformatics analysis. YZ drafted the manuscript. YC and KH drew the figures. ZY and YD prepared the tables. HC and YZ reviewed and revised the manuscript. All authors contributed to the article and approved the submitted version.
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432_2022_4549_MOESM1_ESM.jpg
Figure S1: Construction of a BM-related genes risk signature. (A) LASSO coefficient profiles for the 22 DEGs. (B) LASSO deviance profiles. (JPG 650 kb)
432_2022_4549_MOESM2_ESM.jpg
Figure S2: Association between BM-related DEGs and immune. (A) Immune cells infiltration between high- and low-risk groups. (B) The relationships between the BMGs and immune infiltration cells. (JPG 5602 kb)
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Zhao, Y., Yin, Z., Huang, K. et al. The basement membrane-related gene signature is associated with immunity and predicts survival accurately in hepatocellular carcinoma. J Cancer Res Clin Oncol 149, 5751–5760 (2023). https://doi.org/10.1007/s00432-022-04549-2
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DOI: https://doi.org/10.1007/s00432-022-04549-2